This article presents a novel approach to the rapid and automated identification of fruit diseases using image processing techniques. Leveraging Convolutional Neural Networks (CNN), the proposed methodology offers a swift and automated method to detect and classify passion fruit disorders. Key processes involved in the suggested approach include receiving input photos, pre-processing them, identifying affected areas, highlighting them, confirming the training set, and displaying the results.